Visualization & Data Management

Scientific visualization plays an important role in the scientific process:
to “see the unsee-able”; as the most visible element of scientific research; and
as the visual component of day-to-day diagnostic and exploration tools. Its aim
is to help scientists gain insight into structures, relationships, and anomalies
“hidden” within data. Understanding the science behind ultra-scale simulations and
high-throughput experiments requires extracting meaning from data sets of hundreds
of terabytes or more. Parallel visualization can be a useful path to understanding data at this scale but is not without its own challenges especially across our diverse scientific user community. Research in visualization tools and techniques, partnered with the scientific users and dedicated to producing open source tools supported through workshops and other education activities, can significantly accelerate progress.

Visualization Institutes Announced in September 2006

Ultrascale VisualizationThe Institute for Ultrascale Visualization
Assembling the scalable parallel visualization infrastructure needed to enable
knowledge discovery at the petascale and instructing application scientists on
how to best use these tools
Principal Investigator: Kwan-Liu Ma
(ma@cs.ucdavis.edu)
University of California at Davis

Getting the Science out of the DataThe Scientific Data Management Center for Enabling Technologies
Helping scientists spend more time studying
their results and less time managing their data
Principal Investigator: Arie Shoshani
(shoshani@lbl.gov)
Lawrence Berkeley National Laboratory